Dataset documentation
This page explains how the GPXZ dataset is built. To learn more about how to use the gpxz.io API see the API docs.
Overview
The GPXZ elevation dataset is a composite dataset made by combining multiple open sources of elevation data.
Our dataset covers the entire globe:
- Ice-surface elevation is given at the poles.
- Bathymetry (depth below sea level) is included in the dataset. Most GPXZ API endpoints have an option to remove bathymetry and return an elevation of 0 for locations at sea.
Coverage and resolution
The GPXZ dataset starts with a base of ocean depth from GEBCO 2023 and land elevation from the 30m Copernicus data source.
On top of those base sources, high-resolution lidar datasets are layered where available.
Here's how the coverage looks around the world.
- While lidar coverage for your country of interest may look patchy, these source datasets usually prioritise areas where people live and which researchers study.
- Resolution is given in metres, and represents horizontal precision. A 30m dataset will be unable to capture topographic features smaller than 30m.
Basemaps thanks to OpenStreetMap.
Process
The GPXZ dataset is made by layering open elevation sources.
1. Preprocessing
- For sources that have a non-bathymetric elevation values over ocean areas (either sea-surface height or dummy values), this is removed.
- Small holes are filled using kriging. (Large holes will be filled during merging).
- Source-specific preprocessing is done to remove known areas of corruption and noise.
2. Land merge
- Land source rasters are merged using the algorithm described in Petrasova et al (2017). A max merge angle of 2° is used.
3. Ocean merge
- The merged land elevation raster is then merged with bathymetry.
- The algorithm used to merge the land data leaves a zone of intermediary-quality inside the edge of the hi-res raster. This would be a problem bathymetry merging as these datasets are often low resolution, and coastal data is important for many end users.
- Instead, an estimated elevation profile is linearly interpolated from the edge of the land data out to a distance of 1km offshore. Next, a distance-weighted blend is made between this estimated elevation profile and the bathymetry data.
- As a result, the land data is unchanged during this process, preserving the accuracy of the coastline.